Mesh is a San Francisco–based payments and settlement network that connects wallets, blockchains and digital assets so users can pay with any crypto and merchants receive instant stablecoin or fiat.
<div class="content-intro"><p><strong>About Mesh</strong></p> <p>At Mesh, our mission is to enable consumers to pay and be paid with any asset. Today, trillions of dollars in tokenized assets exist but remain largely unusable for everyday commerce. Mesh is bridging this gap by making crypto payments reliable, useful, and ubiquitous. We combine a powerful orchestration engine with a seamless consumer app to unlock liquidity for the world. Backed by leading investors like PayPal Ventures, Paradigm, and Galaxy Ventures, we are building the infrastructure for the next era of the global economy. Join us!</p></div><p><strong>Overview</strong></p> <p>At Mesh, we're building an AI-first company where intelligence is embedded into how we operate, build, and scale. We're looking for an AI Enablement Lead to help drive that transformation by identifying the company's biggest operational bottlenecks, building AI-powered solutions that eliminate friction, and creating systems that unlock leverage across every team.</p> <p>This is a highly cross-functional role at the intersection of Product, Engineering, GTM, and Operations. You'll partner directly with company leaders to solve high-impact business challenges, deploy AI workflows and automations that teams rely on every day, and help redefine how work gets done at Mesh. Beyond building solutions, you'll establish the playbooks, standards, and internal AI infrastructure that enable the entire organization to move faster, operate smarter, and scale more efficiently.</p> <p><strong>What You'll Do</strong></p> <ul> <li>Identify high-impact opportunities where AI can eliminate manual work, accelerate execution, and unlock outsized business value</li> <li>Partner with executives and functional leaders to solve critical operational challenges across the company</li> <li>Design, build, and launch AI-powered workflows, automations, copilots, and internal tools</li> <li>Own initiatives end to end, from opportunity discovery and prioritization to implementation, adoption, and measurement</li> <li>Drive company-wide AI adoption through enablement, training, and hands-on partnership with teams</li> <li>Establish repeatable frameworks, playbooks, and best practices that empower teams to leverage AI effectively</li> <li>Measure and communicate business impact, tying initiatives to efficiency gains, productivity improvements, and adoption</li> <li>Build the foundation of Mesh's AI operating system, including the tools, standards, and infrastructure that will shape how the company operates for years to come</li> </ul> <p><strong>Who You Are</strong></p> <ul> <li>3+ years of experience in operations, solutions engineering, technical program management, consulting, or similarly cross-functional roles</li> <li>A proven builder who can identify high-impact opportunities, navigate ambiguity, and deliver scalable solutions from concept to execution</li> <li>Strong business and technical judgment, with the ability to translate operational challenges into practical AI-powered solutions</li> <li>Hands-on experience with AI tools and technologies, including LLMs, prompt engineering, agents, APIs, and workflow automation</li> <li>Experience building automations, integrations, internal tooling, and workflow orchestration using APIs, webhooks, and modern AI platforms</li> <li>Experience with data infrastructure, analytics tooling, and measuring business impact through data</li> <li>Experience partnering with senior leaders, influencing across teams, and driving adoption of new tools, systems, or ways of working</li> <li>A systems thinker who enjoys creating repeatable processes, playbooks, and infrastructure that scale</li> <li>Experience in high-growth startup environments (Series A–C preferred)</li> </ul> <p>The annual base salary range for this role is $140,000-$175,000 in San Francisco and New York. The compensation range provided may span multiple career levels and will be narrowed during the interview process based on factors including a candidate’s experience, skills, qualifications, and geographic location. For candidates outside of San Francisco and New York, compensation will be adjusted to reflect the applicable market and location-based pay band. The base salary range listed excludes commission (if applicable), equity, and benefits. The pay range represents the minimum and maximum target for new-hire compensation. Actual compensation may vary and may be higher or lower depending on individual circumstances.</p><div class="content-conclusion"><p><strong>Why You’ll Love It Here</strong></p> <p>At Mesh, you're not stepping into a typical role—you're joining a rocket ship in mid-liftoff. You'll tackle complex, meaningful problems that actually move an industry forward, working alongside a sharp, motivated team that moves quickly, collaborates deeply, and expects everyone to operate with ownership. This is the kind of place where you'll see your work ship fast, make real impact, and be able to point to something and say, "I built that." You'll grow fast, level up your skills, and get a front-row seat to how a high-growth company scales from the inside, with competitive comp, solid benefits, and room to stretch your craft all coming standard. If you're energized by building, learning, and shaping something big—this is where you'll want to be.</p> <p><strong>In-Office Expectations</strong></p> <p>Employees based in our <strong>San Francisco, New York, and Bangalore</strong> hubs are expected to work from the office at least 40% of the time (approximately two days per week). This expectation may vary slightly depending on role, team, and business needs. Certain roles that require closer cross-functional collaboration or operational support may have additional in-office requirements, which will be discussed during the interview process. Our hybrid approach is designed to balance meaningful in-person collaboration, team building, and real-time decision-making with the flexibili